.png){kind=icon}
返回
XGBoost algorithm assisted multi-component quantitative analysis with Raman spectroscopy
.png){kind=icon}
PRE
AI
DOI：10.1016/j.saa.2024.124917.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
To improve prediction performance and reduce artifacts in Raman spectra, we developed an eXtreme Gradient Boosting (XGBoost) preprocessing method to preprocess the Raman spectra of glucose, glycerol and ethanol mixtures. To ensure the robustness and reliability of the XGBoost preprocessing method, an X-LR model (which combined XGBoost preprocessing and a linear regression (LR) model) and a X-MLP model (which combined XGBoost preprocessing and a multilayer perceptron (MLP) model) were developed. These two models were used to quantitatively analyze the concentrations of glucose, glycerol and ethanol in the Raman spectra of mixed solutions. The proportion map of hyperparameters was firstly used to narrow down the search range of hyper- parameters in the X-LR and the X-MLP models. Then the correlation coefficients (R2), 2 ), root mean square of calibration (RMSEC), and root mean square error of prediction (RMSEP) were used to evaluate the models' performance. Experimental results indicated that the XGBoost preprocessing method achieved higher accuracy and generalization capability, with better performance than those of other preprocessing methods for both LR and MLP models.
Keyword:
XGBoost
Raman spectroscopy
Linear regression
Multilayer perceptron
Glucose
期刊
IF:
4.6
论文数:
2.4W
被引数:
5.5W
机构
引用论文
High-resolution, broad-spectral-range Raman measurement using a spatial heterodyne spectrometer with separate filters and multi-gratings.png)
OPTICS EXPRESS
OAAI
OPTICS EXPRESSIF3.3
OAAI分享收藏New data preprocessing trends based on ensemble of multiple preprocessing techniques基于多种预处理技术集成的数据预处理新趋势
OAAI
OAAI分享收藏Quantitative analysis of Raman spectra for glucose concentration in human blood using Gramian angular field and convolutional neural network基于Gramian角场和卷积神经网络的人体血液中葡萄糖浓度拉曼光谱定量分析
PREAI
分享收藏Dimensionless Form of the Double Logarithmic Equation relating Shear Stress to Shear Rate as applied to Slowly Coagulating MilkNature
NatureIF0
PREAI
分享收藏Diagnostic and monitoring applications using near infrared (NIR) spectroscopy in cancer and other diseases使用近红外 (NIR) 光谱在癌症和其他疾病中的诊断和监测应用OAAI
OAAI分享收藏
查看更多内容